Machine learning - Bayesian optimization and multi-armed bandits
Bayesian optimization, Thompson sampling and multi-armed bandits. Applications to algorithm configuration, intelligent user interfaces, advertising, control and other decision problems. Slides available at: http://www.cs.ubc.ca/~nando/540-2013/lectures.html Course taught in 2013 at UBC by Nando de Freitas
Keras documentation: KerasTuner
KerasTuner Star KerasTuner is an easy-to-use, scalable hyperparameter optimization framework that solves the pain points of hyperparameter search. Easily configure your search space with a define-by-run syntax, then leverage one of the available search algorithms to find the best hyperparameter values for your models. KerasTuner comes with Bayesian Optimization, Hyperband, and Random Search algori
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Hyperparameter tuning in Cloud Machine Learning Engine using Bayesian Optimization | Google Cloud Blog
[Tutorial] Bayesian Optimization with LightGBM
Bayesian optimization with skopt — scikit-optimize 0.8.1 documentation
GitHub - scikit-optimize/scikit-optimize: Sequential model-based optimization with a `scipy.optimize` interface
